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Near-optimal estimation of jump activity in semimartingales

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  • Adam D. Bull

Abstract

In quantitative finance, we often model asset prices as semimartingales, with drift, diffusion and jump components. The jump activity index measures the strength of the jumps at high frequencies, and is of interest both in model selection and fitting, and in volatility estimation. In this paper, we give a novel estimate of the jump activity, together with corresponding confidence intervals. Our estimate improves upon previous work, achieving near-optimal rates of convergence, and good finite-sample performance in Monte-Carlo experiments.

Suggested Citation

  • Adam D. Bull, 2014. "Near-optimal estimation of jump activity in semimartingales," Papers 1409.8150, arXiv.org, revised Jan 2016.
    • Handle: RePEc:arx:papers:1409.8150
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    References listed on IDEAS

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    1. Zhao, Zhibiao & Wu, Wei Biao, 2009. "Nonparametric inference of discretely sampled stable Lévy processes," Journal of Econometrics, Elsevier, vol. 153(1), pages 83-92, November.
    2. Cecilia Mancini, 2009. "Non‐parametric Threshold Estimation for Models with Stochastic Diffusion Coefficient and Jumps," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(2), pages 270-296, June.
    3. Lee, Suzanne S. & Hannig, Jan, 2010. "Detecting jumps from Lévy jump diffusion processes," Journal of Financial Economics, Elsevier, vol. 96(2), pages 271-290, May.
    4. Jing, Bing-Yi & Kong, Xin-Bing & Liu, Zhi & Mykland, Per, 2012. "On the jump activity index for semimartingales," Journal of Econometrics, Elsevier, vol. 166(2), pages 213-223.
    5. Adam D. Bull, 2013. "Estimating time-changes in noisy L\'evy models," Papers 1312.5911, arXiv.org, revised Nov 2014.
    6. Barndorff-Nielsen, Ole E. & Graversen, Svend Erik & Jacod, Jean & Shephard, Neil, 2006. "Limit Theorems For Bipower Variation In Financial Econometrics," Econometric Theory, Cambridge University Press, vol. 22(4), pages 677-719, August.
    7. Jing, Bing-Yi & Kong, Xin-Bing & Liu, Zhi, 2011. "Estimating the Jump Activity Index Under Noisy Observations Using High-Frequency Data," Journal of the American Statistical Association, American Statistical Association, vol. 106(494), pages 558-568.
    8. Antonis Papapantoleon, 2008. "An introduction to L\'{e}vy processes with applications in finance," Papers 0804.0482, arXiv.org, revised Nov 2008.
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    Cited by:

    1. Todorov, Viktor, 2019. "Nonparametric inference for the spectral measure of a bivariate pure-jump semimartingale," Stochastic Processes and their Applications, Elsevier, vol. 129(2), pages 419-451.
    2. José E. Figueroa-López & Ruoting Gong & Yuchen Han, 2022. "Estimation of Tempered Stable Lévy Models of Infinite Variation," Methodology and Computing in Applied Probability, Springer, vol. 24(2), pages 713-747, June.
    3. Jos'e E. Figueroa-L'opez & Ruoting Gong & Yuchen Han, 2021. "Estimation of Tempered Stable L\'{e}vy Models of Infinite Variation," Papers 2101.00565, arXiv.org, revised Feb 2022.
    4. B. Cooper Boniece & Jos'e E. Figueroa-L'opez & Yuchen Han, 2022. "Efficient Volatility Estimation for L\'evy Processes with Jumps of Unbounded Variation," Papers 2202.00877, arXiv.org.
    5. Fabian Mies & Ansgar Steland, 2019. "Nonparametric Gaussian inference for stable processes," Statistical Inference for Stochastic Processes, Springer, vol. 22(3), pages 525-555, October.

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